Search Results - (( _ (constructive OR constructing) method algorithm ) OR ( using vector method algorithm ))
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Optimized feature construction methods for data summarizations of relational data
Published 2014“…In this thesis, novel feature construction methods are introduced and a question of whether or not the descriptive accuracy of the summarized data can benefit from the novel feature construction methods is investigated. …”
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Thesis -
2
A parallel version of a binary method and vector addition chains precomputation for exponentiation in RSA / Siti Khatijah Nor Abdul Rahim and Siti Rozanae Ismail
Published 2006“…However, we also constructed an algorithm for a parallel version of Vector Addition Chains to enhance the performance. …”
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Research Reports -
3
Novel vector control method for three-stage hybrid cascaded multilevel inverter
Published 2011“…The inverter has been constructed, and the control algorithm has been implemented. …”
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4
An enhanced distance vector-hop algorithm using new weighted location method for wireless sensor networks
Published 2020“…Next, in order to reduce average hop distance error, a weighted coefficient based on beacon node hop count was constructed. A new weighted least squares method was embedded to solve nonlinear equation problem. …”
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B-spline curve fitting with different parameterization methods
Published 2020“…This research is only focused on B-spline curve and four parameterization methods. In addition, uniformly spaced and averaging knot vector generations are used in generating the knot vector. …”
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Final Year Project / Dissertation / Thesis -
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Feedforward neural network for solving particular fractional differential equations
Published 2024“…This research aims to develop a scheme based on a feedforward neural network (FNN) with a vectorized algorithm (FNNVA) for solving FDEs in the Caputo sense (FDEsC) using selected first-order optimization techniques: simple gradient descent (GD), momentum method (MM), and adaptive moment estimation method (Adam). …”
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Training data selection for record linkage classification
Published 2023“…Random forest and support vector machine classification algorithms were compared, and random forest with the top and imbalanced construction produced an F1 -score comparable to probabilistic record linkage using the expectation maximisation algorithm and EpiLink. …”
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Automated system for concrete damage classification identification using various classification techniques in machine learning / Nur Haziqah Mat ... [et al.]
Published 2021“…Reinforced concrete is the most widely used material for Malaysian building construction. …”
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Conference or Workshop Item -
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Non-fiducial based electrocardiogram biometrics with kernel methods
Published 2017“…A new non-fiducial approach is proposed for feature extraction. This approach constructs an algorithm by combining autocorrelation (AC) and Kernel Principal Component Analysis (KPCA) techniques. …”
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12
Gradient method with multiple damping for large-scale unconstrained optimization
Published 2019“…That is, the proposed method is constructed by combining damping with line search strategies, in which an individual adaptive parameter is proposed to damp the gradient vector while line searches are used to reduce the function value. …”
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Heuristic optimization-based wave kernel descriptor for deformable 3D shape matching and retrieval
Published 2018“…The advantage of the enhanced method comes from the tuning of the variance parameter using MPSO and the selection of the first vector from the constructed OWKS at its first energy scale, thus giving rise to substantially better matching and retrieval accuracy for deformable 3D shape. …”
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Heuristic optimization-based wave kernel descriptor for deformable 3D shape matching and retrieval
Published 2018“…The advantage of the enhanced method comes from the tuning of the variance parameter using MPSO and the selection of the first vector from the constructed OWKS at its first energy scale, thus giving rise to substantially better matching and retrieval accuracy for deformable 3D shape. …”
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15
The capabilities of Multiclass Support Vector Machine (MSVM) training algorithms in grading agarwood essential oil
Published 2024“…This paper purposes to proof the capabilities of multiclass support vector machine (MSVM) training algorithms in grading agarwood essential oil. …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Feature selection methods such as Boruta, Random Forest (RF), Elastic Net (EN), Recursive Feature Elimination (RFE), learning vector quantization (LVQ), Genetic Algorithm (GA), Cluster Dendrogram (CD), Support Vector Machine (SVM) and Logistic Regression (LR) were combined with RF, SVM, LR, and EN classifiers for 30-day mortality prediction. …”
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Automated recognition of Ficus deltoidea using ant colony optimization technique
Published 2013“…This paper presents innovative method to improve the accuracy of classification as well the efficiency, such that irrelevant features that make computational complexity are ignored by feature subset selection that is proposed by means of ant colony optimization algorithm (ACO). …”
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Conference or Workshop Item -
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Web service applications and consumer environments based on ICT-driven optimization
Published 2022“…Therefore, this paper proposes a service recommendation model based on the hybrid embedding of multiple networks and designs a multinetwork hybrid embedding recommendation algorithm. First, the user social relationship network and the user service heterogeneous information network are constructed; then, the embedding vectors of users and services in the same vector space are obtained through multinetwork hybrid embedding learning; finally, the representation vectors of users and services are applied to recommend services to target users. …”
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Reproducing kernel Hilbert space method for cox proportional hazard model
Published 2016“…This algorithm is used to determine the vector i a that enables us to find the optimal parameters of ƒ(x)which is simplified as F(x)= ∑aᵢK(x,xᵢ) . …”
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Thesis -
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Towards large scale unconstrained optimization
Published 2007“…A simple restart procedure for the SR1 method using the standard line search to avoid the loss of positive definiteness will be implemented. …”
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